voidism / ear Goto Github PK

Hello, I am interested in your work, but I have some questions about your paper, for example, GAR best query which uses the ground truth label. I actually don't know the detail about this. use BM25 will get a similar score between the query expansions with Wikipedia, and then how can I get the best query with ground truth?

Hello, I am interested in your work. but i downloaded the data from Google Drive but i see the same missing file to evaluate the model after training,
For example
FileNotFoundError: [Errno 2] No such file or directory: 'output_bm25_gar-sentence-nq-test/nq-test-0/results.json'

When I attempted to construct the training data, I encountered a memory overflow (128GB) when performing bm25 retrieval iteratively on CPU. The memory is rapidly increased in the loop proccess. So I would like to ask how to solve it. Thanks.